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Internet video streaming applications have been demanding more bandwidth and higher video quality, especially with the advent of virtual reality and augmented reality appli-cations. While adaptive strea ming protocols like MPEG-DASH (dynamic adaptive streaming over HTTP) allows video quality to be flexibly adapted, e.g., degraded when mobile network condition deteriorates, this is not an option if the application itself requires guaranteed 4K quality at all time. On the other hand, conventional end-to-end transmission control protocol (TCP) has been struggling in supporting 4K video delivery across long-distance Internet paths containing both fixed and mobile network segments with heterogeneous characteristics. In this paper, we present a novel and practically feasible system architecture named MVP (mobile edge virtualization with adaptive prefetching), which enables content providers to embed their content intelligence as a virtual network function into the mobile network operator's infrastructure edge. Based on this architecture, we present a context-aware adaptive video prefetching scheme in order to achieve quality of experience (QoE)-assured 4K video on demand (VoD) delivery across the global Internet. Through experiments based on a real LTE-A network infrastructure, we demonstrate that our proposed scheme is able to achieve QoE-assured 4K VoD streaming, especially when the video source is located remotely in the public Internet, in which case none of the state-of-the-art solutions is able to support such an objective at global Internet scale.

Due to dynamic wireless network conditions and heterogeneous mobile web content complexities, web-based content services in mobile network environments always suffer from long loading time. The new HTTP/2.0 protocol only adopts one single TCP connection, but recent research reveals that in real mobile environments, web downloading using single connection will experience long idle time and low bandwidth utilization, in particular with dynamic network conditions and web page characteristics. In this paper, by leveraging the Mobile Edge Computing (MEC) technique, we present the framework of Mobile Edge Hint (MEH), in order to enhance mobile web downloading performances. Specifically, the mobile edge collects and caches the meta-data of frequently visited web pages and also keeps monitoring the network conditions. Upon receiving requests on these popular webpages, the MEC server is able to hint back to the HTTP/2.0 clients on the optimized number of TCP connections that should be established for downloading the content. From the test results on real LTE testbed equipped with MEH, we observed up to 34.5% time reduction and in the median case the improvement is 20.5% compared to the plain over-the-top (OTT) HTTP/2.0 protocol.

In this paper, the design, construction, and testing of a fully-functional virtualised mobile core network is outlined. Lessons learned and recommendations for future improvements are provided. The presented work uses open-source software for virtual network function infrastructure control (OpenStack), network flow programming (OpenDaylight), and network orchestration (OpenBaton) to virtualise a commercial software evolved packet core solution deployed on common off-the-shelf hardware. The findings presented in this paper prove the concept of function virtualisation for mobile networks, and paves the way towards future mobile core network function flexibility as required for 5G networks. The paper provides researchers and network operators with first-hand experience to help build similar virtual mobile network infrastructures, and highlights the challenges to tackle and the issues to address to harness the power of virtualisation in 5G networks.